Road Network Based Adaptive Query Evaluation in VANET

Self-organized AdHoc networks have become one of the most interested and studied domains, especially with the rapid development of communication technologies and electronic devices. These networks regroup wireless and self-configuring nodes that communicate independently without a fixed infrastructure. Many applications operate with the AdHoc network due to its rapid deployment and low costs. Security in AdHoc networks is a crucial aspect that protects the exchanges between users and improves network performances. In this paper, a presentation of three AdHoc networks: MANET (Mobile AdHoc Network), VANET (Vehicle AdHoc Network), and FANET (Flaying AdHoc Network) is performed with the focus on their security issues. The paper blends the security requirements and the different attacks faced to the three reviewed networks.

Vehicle Ad-hoc Network (VANET) is a kind of Mobile Ad-hoc Network (MANET) that establishes wireless connection between cars. In VANETs and MANETs, the topology of the network changes very often, therefore implementation of efficient routing protocols is very important problem. In MANETs, the Random Waypoint (RW) model is used as a simulation model for generating node mobility pattern. On the other hand, in VANETs, the mobility patterns of nodes is restricted along the roads, and is affected by the movement of neighbour nodes. In this paper, we present a simulation system for VANET called CAVENET (Cellular Automaton based Vehicular NETwork). In CAVENET, the mobility patterns of nodes are generated by an 1-dimensional cellular automata. We improved CAVENET and implemented some routing protocols. We investigated the performance of the implemented routing protocols by CAVENET. The simulation results have shown that DYMO protocol has better performance than AODV and OLSR protocols.

Vehicle Ad-hoc Networks (VANETs) have recently become an active research area. This is because of its important applications in the transportation field in which vehicles have severe position during activities of daily living in persons. In this paper, the basic background of the VANET from the Intelligent Transportation System (ITS), Mobile Ad-hoc Networks (MANETs), VANET standard and VANET characteristics are discussed. Second, the architecture from components and communications of the system are presented. Then, the critical challenges and future perspectives in this field are comprehensively reviewed. This paper could serve as a guide and reference in the design and development of any new techniques for VANETs. Moreover, this paper may help researchers and developers in the selection of the main features of VANET for their goals in one single document.

Vehicle Ad-Hoc Networks (VANETs) are a special type of Mobile Ad-Hoc Network (MANETs). In VANETs, a group of vehicles communicates with each other to transfer data without a need for a fixed infrastructure. In this paper, we compare the performance of two routing protocols: Ad-hoc on Demand Distance Vector protocol (AODV) and Destination-Sequenced Distance Vector protocol (DSDV) in VANETs. We measure the reliability of each protocol in the packet delivery.

Vehicle Ad hoc Networks (VANETs) are an emergent wireless communication technology that has the potential to reduce the risk of accidents caused by drivers and provide a wide range of entertainment facilities. Because of the nature of VANETs' open-access environment, security attacks can affect the messages broadcast by a vehicle. VANET is therefore vulnerable to security and privacy issues. Recently, many schemes for addressing these problems of VANET have been proposed. However, most of them are affected by massive computation overhead and security issues. In this paper, we propose a scheme named efficient conditional privacy preservation with mutual authentication to address the problems mentioned above in VANET. This scheme depends on the division of geographical areas into a number domains and their distribution, where each domain stores the Certificate Revocation List (CRL) in all Road-side Units (RSUs) located inside the domain. During the mutual authentication phase, the vehicle should authenticate with the TA. After the vehicle obtains a pool of pseudo-identities and the corresponding secret keys from RSU, it is allowed to transmit a message to the other components in the VANET. Because our scheme does not use the bilinear pairing, the performance evaluation shows that our scheme has a lower system cost in terms of computation and communication than other existing methods. Meanwhile, the proposed scheme reduces the computation costs of signing the message and verifying the message by 99.85% and 99.93%, respectively. While the proposed scheme reduces the communication costs of the message size by 13.3%.

Vehicle Ad Hoc Network (VANET) is a type of wireless network consisting of vehicles and roadside communication devices. As VANET is associated with life-critical applications, it is important to consider each component of VANET design, functionality, software, and problems before introducing them. The important goal of VANET is to offer seamless communication for people traveling on the road to collect and relay message from every nearby vehicles in the event of urgent situations such as severe traffic jams, collisions, lane shift, speed limit, hazard or road condition alerts, position alert services, and in the event of climatic disasters, etc. Due to the high mobility of the vehicles, frequent network disconnection happens and many problems emerge in VANETs such as routing, synchronization, network congestion, network control, information management, privacy, security, etc. This chapter reviews the current state of the research on recent artificial intelligence techniques based VANET routing. The chapter also addresses on-going research works on the usage of artificial intelligence techniques for routing in VANET and future challenges need to be addressed in providing the artificial intelligence techniques for routing in VANETs.

This paper reports experimental results on self-organizing wireless networks carried by small flying robots. Flying ad hoc networks (FANETs) composed of small unmanned aerial vehicles (UAVs) are flexible, inexpensive and fast to deploy. This makes them a very attractive technology for many civilian and military applications. Due to the high mobility of the nodes, maintaining a communication link between the UAVs is a challenging task. The topology of these networks is more dynamic than that of typical mobile ad hoc networks (MANETs) and of typical vehicle ad hoc networks (VANETs). As a consequence, the existing routing protocols designed for MANETs partly fail in tracking network topology changes. In this work, we compare two different routing algorithms for ad hoc networks: optimized link-state routing (OLSR), and predictive-OLSR (P-OLSR). The latter is an OLSR extension that we designed for FANETs; it takes advantage of the GPS information available on board. To the best of our knowledge, P-OLSR is currently the only FANET-specific routing technique that has an available Linux implementation. We present results obtained by both Media Access Control (MAC) layer emulations and real-world experiments. In the experiments, we used a testbed composed of two autonomous fixed-wing UAVs and a node on the ground. Our experiments evaluate the link performance and the communication range, as well as the routing performance. Our emulation and experimental results show that P-OLSR significantly outperforms OLSR in routing in the presence of frequent network topology changes.

Vehicle Ad Hoc Network (VANET) created between vehicles or between vehicles and centralized infrastructures is a dynamic network. Specifically, VANET can support many services such as safety, traffic management, and user-oriented services to improve transportation efficiency. Medium Access Control (MAC) protocol in VANETs not only responds the different requirements of these services but also improves the efficient broadcasting safety messages. One such protocol is to employ both TDMA and CSMA schemes in the Control CHannel (CCH), called a hybrid MAC protocol. A vehicle will send safety message without collision on the TDMA-based period during its reserved time slot and utilize the SCH resources on the CSMA-based period for the non-safety message. In addition, the TDMA-based period can be adjusted according to vehicle density. Hence, these systems can adapt themselves to various traffic conditions and improve the throughput for safety messages. In this survey, we compare different hybrid MAC protocols using dynamic TDMA-based periods as well as their benefits and limitations. Finally, we discuss some issues and promising future research which can be satisfied different QoS requirements and efficiently support both safety and non-safety services.

It is a challenging issue to provide a secure and conditional anonymous authentication scheme in vehicle ad hoc networks (VANETs) with low storage space and computational cost. In 2008, Lu et al. proposed a conditional privacy preservation scheme called efficiency conditional privacy preservation (ECPP) protocol. The ECPP protocol provides conditional privacy preservation to vehicles in VANETs. That is, on one hand vehicles can achieve anonymous authentication in the network, on the other hand, allow to be traced and revoked if necessary. However, ECPP scheme suffers from high computational cost and large storage. In this scheme, an improved protocol based on the concept of ECPP protocol has been proposed to achieve more efficiency conditional privacy preservation (MECPP) scheme in VANETs. Comparing with ECCP, the computational cost of the proposed scheme has been decreased by about 54 % while the communication overhead has been reduced by about 10 % . At the same time, a lot of storage space has been saved.

VANET (Vehicle Ad-Hoc Network) is one of the new technologies in the communication system. It supports inter-vehicle communication through the 802. 11p.Many studies have looked at improving the quality of the communication system in VANET. Optimization and effectiveness issues in VANET are still open to exploration. Some researchers have used the natural-inspired algorithm to accomplish the issues in the VANET environment. Many tools can be used as a VANET simulator. While they are helpful, only some of these tools can be used for sophisticated analysis. It can support in-depth analysis or good graphical user interface features. But they cannot be thoroughly combined now. Each simulator has a different characteristic to produce a result. It helps to make a realistic traffic model in VANET. In this paper, we provide a brief information about the VANET communication systems, simulators and models.

Vehicle Ad Hoc Networks (VANETs) are considered to be a next big thing that will remarkably change our lives, since this kind of technology is able to make our lives and roads safer. Intrusion Detection Systems (IDS) is an important technology that can mitigate both inner and outer threats for the vulnerable networks like VANETs. However, it is difficult to adopt the same IDSs that have been appropriately used in wired networks, due to the fast moving and highly dynamic nature of VANETs. Thus, in this article, an Efficient and Collaborative Framework with a Markov-based Reputation Scheme is proposed, namely ECF-MRS. In the proposed framework, the collaborative mechanism is achieved by using Non-dominant Sorting Genetic Algorithm-III (NSGA-III)-Collaboration to merge the advantages of IDSs in VANETs to generate a more superior IDS, while Non-Linear Programming (NLP)-Optimization is designed as the efficient mechanism to reduce the execution time of IDSs in VANETs. Moreover, considering the security risks of collaboration, a Reputation Scheme based on the Hidden Generalized Mixture Transition Distribution (HgMTD) model, namely RS-HgMTD, is proposed for each vehicle in VANETs to evaluate the creditworthiness of their neighbors. Experiments show that the IDS with ECF-MRS has better performance than other existing IDSs in terms of detection rate, detection time and overhead.

Distributed collaborative intrusion detection system for vehicular Ad Hoc networks based on invariant

The increasing number of road vehicles results in more fatalities and accidents. Thus, the manufacturing industry is working on driver safety to secure and safe transportation in Vehicle Ad hoc networks. In addition, the mobile vehicles run in the geographical zone and communicate roadside units over the wireless medium with a certain radius. The Internet of Vehicles has become a new network type where vehicles communicate with the application over public networks. This results in an increase in data exploration and threats related to network security. We propose the deep reinforcement learning method to sensitize the private information for a given vehicle connect over Vehicle Ad hoc networks, maintaining a balance between security and privacy through any sanitization process. Furthermore, we provide a set of recommendations and potential applications for the Vehicle Ad hoc networks as use cases.

With the rapid development and the extensive application of Vehicle Ad Hoc Networks (VANET), the problem of ensuring the credibility of accessing VANET has gained more and more attentions. In the view of the characteristics that the rough set theory is good at handling uncertainly information, we proposed a new approach to access VANET based on rough set theory. We introduced the Mobile Trusted Module (MTM), so the trusted attributes could be gathered, and leading to easily making access decision. Simulations prove the effectiveness and practicality of the presented scheme.

The implementation of intelligent driving technology is inseparable from reliable wireless communication and efficient cache scheduling in Vehicle Ad-hoc Networks (VANETs). The purpose of cache scheduling in VANETs is to provide efficient and fast data services to vehicles. In response to difficult to handle wireless communication interference and high requirements for communication delay and energy consumption optimization in vehicle-road cooperation, we propose a new communication model of “Retrieving-Cast” to simplify the cache scheduling process oriented by data requirements. In V2I mode, consider the uplink of all roadside units(RSUs) retrieving data from vehicles, and prioritize data retrieving based on factors such as the number, density, and urgency of vehicles within the communication coverage range of RSUs. We hope that as many high-priority RSUs as possible to complete cached data retrieving as soon as possible under wireless communication interference. To overcome the limitations of traditional heuristic algorithms with low scheduling efficiency and deep learning methods requiring a large amount of training data, we propose a double-<inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\varepsilon$</tex-math></inline-formula> online reinforcement learning method, which efficiently solves the cache retrieval scheduling problem. Through experiments and analysis, our method achieved better scheduling results compared to traditional approximation algorithms and single <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\varepsilon$</tex-math></inline-formula>-greedy Deep Q-learning methods. The designed data transformation method also addresses the issue of requiring a large amount of training data, enabling rapid computation of scheduling requests in the network at an extremely low training cost, meeting the low-latency computation requirements in VANETs.